Massive MIMO Joint Communications and Sensing with MRT Beamforming

Joint communications and sensing (JCAS) is en-visioned as a key feature in future wireless communications networks. In massive MIMO-JCAS systems, the very large number of antennas causes excessively high computational complexity in beamforming designs. In this work, we investigate a low-complexity massive multiple-input-multiple-output (MIMO)-JCAS system employing the maximum-ratio transmission (MRT) scheme for both communications and sensing. We first derive closed-form expressions for the achievable communications rate and Cramer-Rao bound (CRB) as functions of the large-scale fading channel coefficients. Then, we develop a power allocation strategy based on successive convex approximation to maximize the communications sum rate while guaranteeing the CRB con-straint and transmit power budget. Our analysis shows that the introduction of sensing functionality increases the beamforming uncertainty and inter-user interference on the communications side. However, these factors can be mitigated by deploying a very large number of antennas. The numerical results verify our findings and demonstrate the power allocation efficiency.